Merge 7fc8e11f58 into de3188fb1f

3 weeks ago · 8c6c5fcfc8
parent de3188fb1f 7fc8e11f58
commit 8c6c5fcfc8
21 changed files with 2054 additions and 0 deletions
--- a/graph/index.html
+++ b/graph/index.html
@ -0,0 +1,313 @@
+<!doctype html>
+<html lang="zh-CN">
+<head>
+  <meta charset="utf-8">
+  <meta name="viewport" content="width=device-width, initial-scale=1">
+  <title>Human System Optimization Knowledge Graph</title>
+  <script src="../skill/references/graph-data.js"></script>
+  <style>
+    :root {
+      color-scheme: light;
+      --bg: #f7f7f2;
+      --ink: #18221f;
+      --muted: #5f6862;
+      --line: #cfd8d1;
+      --module: #2f6f73;
+      --practice: #6d8f3f;
+      --mechanism: #6a5b9a;
+      --risk: #a6503d;
+      --panel: #ffffff;
+    }
+
+    * {
+      box-sizing: border-box;
+    }
+
+    body {
+      margin: 0;
+      min-height: 100vh;
+      background: var(--bg);
+      color: var(--ink);
+      font-family: Inter, ui-sans-serif, system-ui, -apple-system, BlinkMacSystemFont, "Segoe UI", sans-serif;
+    }
+
+    header {
+      display: grid;
+      grid-template-columns: minmax(0, 1fr) auto;
+      gap: 16px;
+      align-items: end;
+      padding: 24px 28px 16px;
+      border-bottom: 1px solid var(--line);
+      background: #fbfbf7;
+    }
+
+    h1 {
+      margin: 0;
+      font-size: 26px;
+      font-weight: 720;
+      letter-spacing: 0;
+    }
+
+    .subtitle {
+      margin: 8px 0 0;
+      color: var(--muted);
+      font-size: 14px;
+      line-height: 1.55;
+    }
+
+    .toolbar {
+      display: flex;
+      gap: 8px;
+      align-items: center;
+    }
+
+    input {
+      width: min(320px, 42vw);
+      border: 1px solid var(--line);
+      border-radius: 8px;
+      padding: 10px 12px;
+      font-size: 14px;
+      background: #fff;
+      color: var(--ink);
+    }
+
+    main {
+      display: grid;
+      grid-template-columns: minmax(0, 1fr) 340px;
+      min-height: calc(100vh - 98px);
+    }
+
+    #graph {
+      width: 100%;
+      height: calc(100vh - 98px);
+      display: block;
+    }
+
+    aside {
+      border-left: 1px solid var(--line);
+      background: var(--panel);
+      padding: 20px;
+      overflow: auto;
+    }
+
+    .legend {
+      display: grid;
+      grid-template-columns: 1fr 1fr;
+      gap: 8px;
+      margin: 18px 0;
+    }
+
+    .legend span {
+      display: inline-flex;
+      gap: 7px;
+      align-items: center;
+      color: var(--muted);
+      font-size: 13px;
+    }
+
+    .dot {
+      width: 10px;
+      height: 10px;
+      border-radius: 50%;
+      display: inline-block;
+    }
+
+    h2 {
+      margin: 0 0 8px;
+      font-size: 18px;
+      letter-spacing: 0;
+    }
+
+    .detail {
+      color: var(--muted);
+      line-height: 1.6;
+      font-size: 14px;
+    }
+
+    .relations {
+      margin-top: 18px;
+      padding-top: 16px;
+      border-top: 1px solid var(--line);
+    }
+
+    .relation {
+      margin: 0 0 12px;
+      font-size: 13px;
+      line-height: 1.5;
+      color: var(--muted);
+    }
+
+    .relation strong {
+      color: var(--ink);
+      font-weight: 650;
+    }
+
+    @media (max-width: 820px) {
+      header {
+        grid-template-columns: 1fr;
+        align-items: start;
+      }
+
+      input {
+        width: 100%;
+      }
+
+      main {
+        grid-template-columns: 1fr;
+      }
+
+      #graph {
+        height: 62vh;
+      }
+
+      aside {
+        border-left: 0;
+        border-top: 1px solid var(--line);
+      }
+    }
+  </style>
+</head>
+<body>
+  <header>
+    <div>
+      <h1>Human System Optimization Knowledge Graph</h1>
+      <p class="subtitle">睡眠、饮食、动力、专注、大脑健康、长寿与个人实践之间的知识关系。</p>
+    </div>
+    <div class="toolbar">
+      <input id="search" type="search" placeholder="搜索节点，例如 睡眠、禁食、多巴胺">
+    </div>
+  </header>
+
+  <main>
+    <svg id="graph" role="img" aria-label="Human System Optimization knowledge graph"></svg>
+    <aside>
+      <h2 id="node-title">选择一个节点</h2>
+      <p id="node-detail" class="detail">点击图中的节点查看说明和相关关系。</p>
+      <div class="legend">
+        <span><i class="dot" style="background: var(--module)"></i>模块</span>
+        <span><i class="dot" style="background: var(--practice)"></i>实践</span>
+        <span><i class="dot" style="background: var(--mechanism)"></i>机制</span>
+        <span><i class="dot" style="background: var(--risk)"></i>风险</span>
+      </div>
+      <div class="relations">
+        <h2>关系</h2>
+        <div id="relations"></div>
+      </div>
+    </aside>
+  </main>
+
+  <script>
+    const graph = window.HSO_GRAPH;
+    const svg = document.getElementById("graph");
+    const search = document.getElementById("search");
+    const title = document.getElementById("node-title");
+    const detail = document.getElementById("node-detail");
+    const relations = document.getElementById("relations");
+    const colors = {
+      module: "#2f6f73",
+      practice: "#6d8f3f",
+      mechanism: "#6a5b9a",
+      risk: "#a6503d"
+    };
+    let selectedId = "sleep";
+
+    function layout(width, height) {
+      const cx = width / 2;
+      const cy = height / 2;
+      const ring = Math.min(width, height) * 0.34;
+      const center = new Set(["sleep", "diet", "dopamine", "focus", "brain", "longevity", "practice"]);
+      const outer = graph.nodes.filter(node => !center.has(node.id));
+      const inner = graph.nodes.filter(node => center.has(node.id));
+
+      inner.forEach((node, index) => {
+        const angle = (Math.PI * 2 * index) / inner.length - Math.PI / 2;
+        node.x = cx + Math.cos(angle) * ring * 0.52;
+        node.y = cy + Math.sin(angle) * ring * 0.52;
+      });
+
+      outer.forEach((node, index) => {
+        const angle = (Math.PI * 2 * index) / outer.length - Math.PI / 2;
+        node.x = cx + Math.cos(angle) * ring;
+        node.y = cy + Math.sin(angle) * ring;
+      });
+    }
+
+    function nodeById(id) {
+      return graph.nodes.find(node => node.id === id);
+    }
+
+    function render() {
+      const width = svg.clientWidth;
+      const height = svg.clientHeight;
+      const query = search.value.trim().toLowerCase();
+      layout(width, height);
+      svg.setAttribute("viewBox", `0 0 ${width} ${height}`);
+      svg.innerHTML = "";
+
+      const edgeLayer = document.createElementNS("http://www.w3.org/2000/svg", "g");
+      graph.edges.forEach(edge => {
+        const source = nodeById(edge.source);
+        const target = nodeById(edge.target);
+        const line = document.createElementNS("http://www.w3.org/2000/svg", "line");
+        line.setAttribute("x1", source.x);
+        line.setAttribute("y1", source.y);
+        line.setAttribute("x2", target.x);
+        line.setAttribute("y2", target.y);
+        line.setAttribute("stroke", "#b9c5bd");
+        line.setAttribute("stroke-width", selectedId === edge.source || selectedId === edge.target ? "2.4" : "1.2");
+        line.setAttribute("opacity", selectedId === edge.source || selectedId === edge.target ? "0.95" : "0.5");
+        edgeLayer.appendChild(line);
+      });
+      svg.appendChild(edgeLayer);
+
+      graph.nodes.forEach(node => {
+        const matched = !query || node.label.toLowerCase().includes(query) || node.detail.toLowerCase().includes(query);
+        const group = document.createElementNS("http://www.w3.org/2000/svg", "g");
+        group.setAttribute("cursor", "pointer");
+        group.setAttribute("opacity", matched ? "1" : "0.22");
+        group.addEventListener("click", () => {
+          selectedId = node.id;
+          updatePanel();
+          render();
+        });
+
+        const circle = document.createElementNS("http://www.w3.org/2000/svg", "circle");
+        circle.setAttribute("cx", node.x);
+        circle.setAttribute("cy", node.y);
+        circle.setAttribute("r", selectedId === node.id ? "30" : "24");
+        circle.setAttribute("fill", colors[node.type]);
+        circle.setAttribute("stroke", selectedId === node.id ? "#18221f" : "#ffffff");
+        circle.setAttribute("stroke-width", selectedId === node.id ? "3" : "2");
+        group.appendChild(circle);
+
+        const label = document.createElementNS("http://www.w3.org/2000/svg", "text");
+        label.setAttribute("x", node.x);
+        label.setAttribute("y", node.y + 42);
+        label.setAttribute("text-anchor", "middle");
+        label.setAttribute("font-size", "13");
+        label.setAttribute("font-weight", selectedId === node.id ? "700" : "560");
+        label.setAttribute("fill", "#18221f");
+        label.textContent = node.label;
+        group.appendChild(label);
+        svg.appendChild(group);
+      });
+    }
+
+    function updatePanel() {
+      const node = nodeById(selectedId);
+      title.textContent = node.label;
+      detail.textContent = node.detail;
+      const connected = graph.edges.filter(edge => edge.source === node.id || edge.target === node.id);
+      relations.innerHTML = connected.map(edge => {
+        const other = nodeById(edge.source === node.id ? edge.target : edge.source);
+        return `<p class="relation"><strong>${other.label}</strong><br>${edge.relation}</p>`;
+      }).join("") || "<p class=\"relation\">暂无关系。</p>";
+    }
+
+    search.addEventListener("input", render);
+    window.addEventListener("resize", render);
+    updatePanel();
+    render();
+  </script>
+</body>
+</html>
--- a/hso/.python-version
+++ b/hso/.python-version
@ -0,0 +1 @@
+3.12
--- a/hso/pyproject.toml
+++ b/hso/pyproject.toml
@ -0,0 +1,26 @@
+[project]
+name = "humansystemoptimization"
+version = "0.1.0"
+description = "Structured knowledge base and MCP server for HumanSystemOptimization"
+requires-python = ">=3.12"
+dependencies = [
+    "mcp>=1.0.0",
+]
+
+[project.scripts]
+hso-mcp = "humansystemoptimization.mcp_server:main"
+
+[build-system]
+requires = ["hatchling"]
+build-backend = "hatchling.build"
+
+[tool.hatch.build.targets.wheel]
+packages = ["src/humansystemoptimization"]
+
+[dependency-groups]
+dev = [
+    "pytest>=8.0.0",
+]
+
+[tool.pytest.ini_options]
+pythonpath = ["src"]
--- a/hso/src/humansystemoptimization/init.py
+++ b/hso/src/humansystemoptimization/init.py
@ -0,0 +1,5 @@
+"""Human System Optimization knowledge tools."""
+
+from humansystemoptimization.knowledge import KnowledgeBase, load_knowledge_base
+
+__all__ = ["KnowledgeBase", "load_knowledge_base"]
--- a/hso/src/humansystemoptimization/knowledge.py
+++ b/hso/src/humansystemoptimization/knowledge.py
@ -0,0 +1,120 @@
+from __future__ import annotations
+
+import json
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any
+
+
+def _default_root() -> Path:
+    return Path(__file__).resolve().parents[3]
+
+
+@dataclass(frozen=True)
+class KnowledgeBase:
+    root: Path
+    data: dict[str, Any]
+
+    def list_modules(self) -> list[dict[str, Any]]:
+        return [
+            {
+                "id": module["id"],
+                "title": module["title"],
+                "summary": module["summary"],
+                "priority": module["priority"],
+                "chapter_path": module["chapter_path"],
+            }
+            for module in self.data["modules"]
+        ]
+
+    def get_module(self, module_id: str) -> dict[str, Any]:
+        for module in self.data["modules"]:
+            if module["id"] == module_id:
+                return module
+        raise KeyError(f"Unknown module_id: {module_id}")
+
+    def search(self, query: str, limit: int = 5) -> list[dict[str, Any]]:
+        tokens = [token.lower() for token in query.split() if token.strip()]
+        if not tokens:
+            return []
+
+        scored: list[tuple[int, dict[str, Any]]] = []
+        for module in self.data["modules"]:
+            haystacks = self._search_fields(module)
+            score = 0
+            matches: list[str] = []
+            for field in haystacks:
+                lowered = field.lower()
+                hits = sum(1 for token in tokens if token in lowered)
+                if hits:
+                    score += hits
+                    matches.append(field)
+            if score:
+                scored.append(
+                    (
+                        score,
+                        {
+                            "module_id": module["id"],
+                            "title": module["title"],
+                            "summary": module["summary"],
+                            "matches": matches[:6],
+                        },
+                    )
+                )
+
+        scored.sort(key=lambda item: (-item[0], self._module_rank(item[1]["module_id"])))
+        return [item for _, item in scored[:limit]]
+
+    def plan_template(self, focus: str = "general") -> dict[str, Any]:
+        focus_id = focus if focus in {module["id"] for module in self.data["modules"]} else "general"
+        selected = [
+            module
+            for module in self.data["modules"]
+            if focus_id == "general" or module["id"] == focus_id
+        ]
+        if focus_id == "general":
+            selected = self.data["modules"][:4]
+
+        return {
+            "focus": focus_id,
+            "medical_boundary": self.data["medical_boundary"],
+            "daily_actions": [
+                {
+                    "module_id": module["id"],
+                    "title": module["title"],
+                    "actions": module["practices"][:3],
+                    "cautions": module["cautions"][:2],
+                }
+                for module in selected
+            ],
+            "tracking_metrics": self.data["tracking_metrics"],
+            "review_cadence": "每 7 天回顾执行难度、睡眠/精力/运动/饮食记录，每 30 天结合身体指标或专业建议调整。",
+        }
+
+    def graph(self) -> dict[str, Any]:
+        return self.data["graph"]
+
+    def references(self) -> list[dict[str, Any]]:
+        return self.data["references"]
+
+    def _module_rank(self, module_id: str) -> int:
+        for index, module in enumerate(self.data["modules"]):
+            if module["id"] == module_id:
+                return index
+        return 10_000
+
+    @staticmethod
+    def _search_fields(module: dict[str, Any]) -> list[str]:
+        fields = [module["title"], module["summary"]]
+        for key in ("mechanisms", "practices", "cautions", "keywords"):
+            fields.extend(module.get(key, []))
+        fields.extend(ref["title"] for ref in module.get("references", []))
+        return fields
+
+
+def load_knowledge_base(root: Path | None = None) -> KnowledgeBase:
+    repo_root = root or _default_root()
+    index_path = repo_root / "skill" / "references" / "index.json"
+    with index_path.open("r", encoding="utf-8") as file:
+        data = json.load(file)
+    return KnowledgeBase(root=repo_root, data=data)
--- a/hso/src/humansystemoptimization/mcp_server.py
+++ b/hso/src/humansystemoptimization/mcp_server.py
@ -0,0 +1,121 @@
+from __future__ import annotations
+
+import argparse
+import json
+from typing import Any
+
+from mcp.server.fastmcp import FastMCP
+
+from humansystemoptimization.knowledge import load_knowledge_base
+
+
+SERVER_NAME = "human-system-optimization"
+
+
+def list_modules_payload() -> dict[str, Any]:
+    kb = load_knowledge_base()
+    modules = kb.list_modules()
+    return {
+        "count": len(modules),
+        "modules": modules,
+        "medical_boundary": kb.data["medical_boundary"],
+    }
+
+
+def search_knowledge_payload(query: str, limit: int = 5) -> dict[str, Any]:
+    kb = load_knowledge_base()
+    return {
+        "query": query,
+        "limit": limit,
+        "results": kb.search(query, limit=limit),
+        "medical_boundary": kb.data["medical_boundary"],
+    }
+
+
+def get_module_payload(module_id: str) -> dict[str, Any]:
+    kb = load_knowledge_base()
+    return {
+        "module": kb.get_module(module_id),
+        "medical_boundary": kb.data["medical_boundary"],
+    }
+
+
+def build_life_plan_payload(focus: str = "general") -> dict[str, Any]:
+    kb = load_knowledge_base()
+    return {
+        "plan": kb.plan_template(focus),
+        "source": kb.data["source"],
+    }
+
+
+def get_graph_payload() -> dict[str, Any]:
+    kb = load_knowledge_base()
+    return {
+        "graph": kb.graph(),
+        "medical_boundary": kb.data["medical_boundary"],
+    }
+
+
+def create_server() -> FastMCP:
+    mcp = FastMCP(SERVER_NAME)
+
+    @mcp.tool()
+    def list_modules() -> dict[str, Any]:
+        """List the structured health habit knowledge modules."""
+        return list_modules_payload()
+
+    @mcp.tool()
+    def search_knowledge(query: str, limit: int = 5) -> dict[str, Any]:
+        """Search the local health habit knowledge base by keyword."""
+        return search_knowledge_payload(query=query, limit=limit)
+
+    @mcp.tool()
+    def get_module(module_id: str) -> dict[str, Any]:
+        """Return one full knowledge module by id."""
+        return get_module_payload(module_id=module_id)
+
+    @mcp.tool()
+    def build_life_plan(focus: str = "general") -> dict[str, Any]:
+        """Build a conservative habit-plan template for a module or general health."""
+        return build_life_plan_payload(focus=focus)
+
+    @mcp.tool()
+    def get_graph() -> dict[str, Any]:
+        """Return knowledge graph nodes and edges."""
+        return get_graph_payload()
+
+    return mcp
+
+
+def _self_test() -> dict[str, Any]:
+    modules = list_modules_payload()
+    graph = get_graph_payload()
+    return {
+        "server": SERVER_NAME,
+        "module_count": modules["count"],
+        "graph_nodes": len(graph["graph"]["nodes"]),
+        "graph_edges": len(graph["graph"]["edges"]),
+        "tools": [
+            "list_modules",
+            "search_knowledge",
+            "get_module",
+            "build_life_plan",
+            "get_graph",
+        ],
+    }
+
+
+def main() -> None:
+    parser = argparse.ArgumentParser(description="HumanSystemOptimization MCP server")
+    parser.add_argument("--self-test", action="store_true", help="Load local knowledge and print a JSON health check.")
+    args = parser.parse_args()
+
+    if args.self_test:
+        print(json.dumps(_self_test(), ensure_ascii=False, indent=2))
+        return
+
+    create_server().run()
+
+
+if __name__ == "__main__":
+    main()
--- a/hso/tests/test_knowledge.py
+++ b/hso/tests/test_knowledge.py
@ -0,0 +1,49 @@
+from pathlib import Path
+
+from humansystemoptimization.knowledge import load_knowledge_base
+
+
+def test_lists_core_modules_in_readme_order():
+    kb = load_knowledge_base(Path(__file__).resolve().parents[2])
+
+    module_ids = [module["id"] for module in kb.list_modules()]
+
+    assert module_ids[:7] == [
+        "sleep",
+        "diet",
+        "mindset_dopamine",
+        "learning_focus",
+        "brain_health",
+        "longevity",
+        "personal_practice",
+    ]
+
+
+def test_search_finds_practices_across_modules():
+    kb = load_knowledge_base(Path(__file__).resolve().parents[2])
+
+    results = kb.search("早晨 阳光 睡眠")
+
+    assert results[0]["module_id"] == "sleep"
+    assert any("起床后" in hit for hit in results[0]["matches"])
+
+
+def test_get_module_preserves_cautions_and_references():
+    kb = load_knowledge_base(Path(__file__).resolve().parents[2])
+
+    module = kb.get_module("longevity")
+
+    assert "Sinclair" in module["summary"]
+    assert any("争议" in caution for caution in module["cautions"])
+    assert any(ref["title"] == "程序员延寿指南" for ref in module["references"])
+
+
+def test_plan_template_returns_actionable_sections_for_focus():
+    kb = load_knowledge_base(Path(__file__).resolve().parents[2])
+
+    plan = kb.plan_template("sleep")
+
+    assert plan["focus"] == "sleep"
+    assert plan["medical_boundary"]
+    assert any(item["module_id"] == "sleep" for item in plan["daily_actions"])
+    assert any("睡眠" in metric for metric in plan["tracking_metrics"])
--- a/hso/tests/test_mcp_server.py
+++ b/hso/tests/test_mcp_server.py
@ -0,0 +1,44 @@
+from humansystemoptimization.mcp_server import (
+    build_life_plan_payload,
+    get_graph_payload,
+    get_module_payload,
+    list_modules_payload,
+    search_knowledge_payload,
+)
+
+
+def test_list_modules_payload_contains_reader_paths():
+    payload = list_modules_payload()
+
+    assert payload["count"] >= 7
+    assert payload["modules"][0]["id"] == "sleep"
+    assert payload["modules"][0]["chapter_path"].startswith("references/modules/")
+
+
+def test_search_knowledge_payload_returns_matches():
+    payload = search_knowledge_payload("发酵 肠道")
+
+    assert payload["query"] == "发酵 肠道"
+    assert payload["results"][0]["module_id"] == "diet"
+
+
+def test_get_module_payload_includes_assets_for_longevity():
+    payload = get_module_payload("longevity")
+
+    assert "imgs/diet_for_longevity.png" in payload["module"]["assets"]
+    assert payload["medical_boundary"]
+
+
+def test_build_life_plan_payload_includes_boundary_and_actions():
+    payload = build_life_plan_payload("learning_focus")
+
+    assert payload["plan"]["focus"] == "learning_focus"
+    assert payload["plan"]["medical_boundary"]
+    assert payload["plan"]["daily_actions"][0]["module_id"] == "learning_focus"
+
+
+def test_get_graph_payload_exposes_nodes_and_edges():
+    payload = get_graph_payload()
+
+    assert any(node["id"] == "sleep" for node in payload["graph"]["nodes"])
+    assert any(edge["target"] == "longevity" for edge in payload["graph"]["edges"])
--- a/hso/uv.lock
+++ b/hso/uv.lock
@ -0,0 +1,703 @@
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--- a/skill/SKILL.md
+++ b/skill/SKILL.md
@ -0,0 +1,76 @@
+---
+name: human-system-optimization
+description: Use when answering questions, teaching concepts, or drafting habit plans from the HumanSystemOptimization daily health practice knowledge base.
+---
+
+# Human System Optimization
+
+Use this skill to help an agent answer questions and draft conservative life plans from this repository's health habit tutorial.
+
+## Source Of Truth
+
+Read these local artifacts before answering:
+
+1. `references/index.json` for machine-readable modules, practices, cautions, references, and graph data.
+2. `references/modules/*.md` for chapter-level explanations.
+3. `README.md` when the user asks for original wording or full context.
+4. `imgs/*.png` when answering about long-term diet, workout plans, longevity drugs, or cell reprogramming visuals.
+
+Optional MCP access:
+
+```bash
+cd hso && uv run hso-mcp
+```
+
+The MCP server exposes:
+
+- `list_modules`
+- `search_knowledge`
+- `get_module`
+- `build_life_plan`
+- `get_graph`
+
+## Answering Rules
+
+- Start from low-risk fundamentals: sleep, morning light, night light reduction, movement, reduced sugar, stable eating window, and focused work blocks.
+- Preserve cautions. If a module has `cautions`, include relevant ones when giving advice.
+- Do not present drugs, supplements, long fasting, or anti-aging interventions as routine recommendations.
+- State that the knowledge base is for learning and habit design, not medical diagnosis or treatment.
+- For medical conditions, abnormal lab values, pregnancy, minors, eating disorders, psychiatric concerns, chronic disease, or medication use, advise consultation with a qualified clinician.
+
+## Planning Workflow
+
+When drafting a plan:
+
+1. Identify the user's focus: `sleep`, `diet`, `mindset_dopamine`, `learning_focus`, `brain_health`, `longevity`, `personal_practice`, or `general`.
+2. Retrieve the module with MCP `get_module` or from `references/index.json`.
+3. Select at most 3 actions for the first week.
+4. Add tracking metrics from `tracking_metrics`.
+5. Add a weekly review checkpoint.
+6. Include relevant cautions and medical boundary text.
+
+## Teaching Workflow
+
+When helping the user absorb the material:
+
+1. Explain the mechanism in plain language.
+2. Give one concrete daily action.
+3. Explain why the action maps to the mechanism.
+4. Name one common failure mode.
+5. Offer a short review question or self-check.
+
+## Module Map
+
+- `sleep`: sleep, circadian rhythm, morning light, night light, caffeine, NSDR.
+- `diet`: intermittent fasting, eating windows, blood glucose, gut microbiome, fermented foods.
+- `mindset_dopamine`: motivation, reward, dopamine baseline, addiction, growth mindset.
+- `learning_focus`: neuroplasticity, errors, physiological sigh, attention, screen time.
+- `brain_health`: aerobic exercise, Omega-3 EPA, choline, creatine, electrolytes.
+- `longevity`: diet, exercise, monitoring, anti-aging drug controversy, cell reprogramming.
+- `personal_practice`: author's practical routine and tool-based habit training.
+
+## Safety Boundary
+
+Use this exact boundary when the user asks for medical or high-risk advice:
+
+> This repository supports health habit learning and planning. It is not a medical diagnosis, prescription, or treatment plan. For medications, supplements, prolonged fasting, chronic illness, abnormal lab values, pregnancy, minors, psychiatric concerns, or eating disorders, involve a qualified clinician.
--- a/skill/references/graph-data.js
+++ b/skill/references/graph-data.js
@ -0,0 +1,38 @@
+window.HSO_GRAPH = {
+  nodes: [
+    { id: "sleep", label: "睡眠", type: "module", detail: "健康、学习、代谢和情绪的基础。" },
+    { id: "diet", label: "饮食/禁食", type: "module", detail: "进食窗口、血糖状态、肠道菌群和饮食结构。" },
+    { id: "dopamine", label: "多巴胺", type: "mechanism", detail: "动机、奖励、快乐阈值和专注协调。" },
+    { id: "focus", label: "学习专注", type: "module", detail: "犯错信号、神经可塑性、休息和注意力环境。" },
+    { id: "brain", label: "大脑健康", type: "module", detail: "有氧运动、Omega-3、胆碱、电解质。" },
+    { id: "longevity", label: "长寿", type: "module", detail: "饮食、运动、监测、药物争议和细胞重编程。" },
+    { id: "practice", label: "个人实践", type: "module", detail: "把知识转成低摩擦日常习惯。" },
+    { id: "light", label: "晨间光照", type: "practice", detail: "起床后户外 2-10 分钟。" },
+    { id: "night_light", label: "夜间避光", type: "practice", detail: "尤其避免 23:00-04:00 强光。" },
+    { id: "fasting", label: "进食窗口", type: "practice", detail: "基础版睡前 2-3 小时不吃，高阶 8 小时窗口。" },
+    { id: "fermented", label: "发酵食品", type: "practice", detail: "每天两次自然发酵食品，支持菌群多样性。" },
+    { id: "exercise", label: "有氧+力量", type: "practice", detail: "每周约 150-180 分钟有氧，搭配力量训练。" },
+    { id: "nsdr", label: "NSDR/冥想", type: "practice", detail: "午休、Yoga Nidra、生理叹息和深度休息。" },
+    { id: "caution_drugs", label: "药物/补剂争议", type: "risk", detail: "NMN、白藜芦醇、二甲双胍、聪明药等需谨慎。" },
+    { id: "medical", label: "医学边界", type: "risk", detail: "药物、慢病、异常指标、极端禁食需要专业意见。" }
+  ],
+  edges: [
+    { source: "light", target: "sleep", relation: "校准昼夜节律" },
+    { source: "night_light", target: "sleep", relation: "降低节律扰动" },
+    { source: "sleep", target: "dopamine", relation: "夜间光照影响后续多巴胺状态" },
+    { source: "dopamine", target: "focus", relation: "支持动机和专注网络协调" },
+    { source: "sleep", target: "focus", relation: "睡眠中巩固学习" },
+    { source: "nsdr", target: "focus", relation: "降低压力并支持学习恢复" },
+    { source: "fasting", target: "diet", relation: "控制进食时间和血糖状态" },
+    { source: "fermented", target: "diet", relation: "提升肠道菌群多样性" },
+    { source: "exercise", target: "brain", relation: "有氧支持大脑供能" },
+    { source: "exercise", target: "longevity", relation: "心肺和肌肉能力支持延寿" },
+    { source: "diet", target: "longevity", relation: "饮食结构和禁食影响衰老机制" },
+    { source: "practice", target: "sleep", relation: "晨光和夜间避光可训练" },
+    { source: "practice", target: "diet", relation: "进食窗口可训练" },
+    { source: "practice", target: "focus", relation: "专注块和阅读可训练" },
+    { source: "caution_drugs", target: "longevity", relation: "抗衰药物证据争议" },
+    { source: "medical", target: "caution_drugs", relation: "涉及药物和异常指标需专业意见" },
+    { source: "medical", target: "fasting", relation: "极端禁食需专业评估" }
+  ]
+};
--- a/skill/references/index.json
+++ b/skill/references/index.json
@ -0,0 +1,281 @@
+{
+  "version": "2026-06-20",
+  "source": "README.md",
+  "medical_boundary": "本知识库用于健康习惯学习、复盘和生活计划辅助，不构成医疗诊断、处方或治疗建议。涉及药物、补充剂、长时间禁食、慢病、孕产、精神健康、未成年人或异常指标时，应咨询医生或合格专业人员。",
+  "tracking_metrics": [
+    "睡眠时长、睡眠质量、入睡时间和夜间光照暴露",
+    "进食窗口、糖和深加工食品摄入、发酵食品和植物性食物摄入",
+    "每周有氧分钟数、力量训练次数、运动后睡眠影响",
+    "专注时段、手机使用时长、学习后的休息和复盘",
+    "体重、腰围、血糖 HbA1c、CRP、LDL 等需要专业解读的指标"
+  ],
+  "modules": [
+    {
+      "id": "sleep",
+      "title": "睡眠与昼夜节律",
+      "summary": "睡眠是健康、免疫、代谢、心理状态、专注和学习的基础。README 将光照、体温、咖啡因、午睡和夜间行为作为调节昼夜节律的主要杠杆。",
+      "priority": 1,
+      "chapter_path": "references/modules/01_sleep.md",
+      "keywords": ["睡眠", "光照", "皮质醇", "褪黑素", "体温", "咖啡因", "Yoga Nidra"],
+      "mechanisms": [
+        "早晨光照通过黑视素神经节细胞校准内在生物钟，并影响皮质醇、肾上腺素和褪黑素倒计时。",
+        "夜间强光会让身体误判为白天，扰乱昼夜节律，并可能影响后续多巴胺、情绪、专注和代谢。",
+        "体温上升倾向于推动清醒，体温下降有利于进入睡眠；运动、冷水澡和环境温度会改变这个节律。"
+      ],
+      "practices": [
+        "起床后到户外接触阳光 2-10 分钟；阴天可适当延长，隔窗效果显著下降。",
+        "晚上减少光源，尤其避免 23:00 到次日 04:00 的强光和手机光。",
+        "傍晚观察落日，帮助身体获得夜间到来的时间信号。",
+        "中午后咖啡因是否影响睡眠需要个人测试；默认应谨慎。",
+        "可用午睡、Yoga Nidra、冥想或自我催眠作为非睡眠深度休息。"
+      ],
+      "cautions": [
+        "不建议把褪黑素作为常规入睡工具；README 提到剂量监管和情绪风险。",
+        "镁、芹黄素、牛磺酸等补充剂应结合自身情况和专业意见。",
+        "晚间高强度运动可能推迟体温下降并影响入睡。"
+      ],
+      "assets": [],
+      "references": [
+        {"title": "Huberman Lab", "url": "https://hubermanlab.com/", "role": "primary inspiration"},
+        {"title": "Yoga Nidra example", "url": "https://youtu.be/M0u9GST_j3s", "role": "practice example"},
+        {"title": "Examine.com", "url": "https://examine.com/", "role": "supplement lookup"}
+      ]
+    },
+    {
+      "id": "diet",
+      "title": "饮食、禁食与肠道健康",
+      "summary": "饮食模块强调何时进食与吃什么同等重要：间歇性禁食影响血糖、修复和代谢状态，发酵食物和植物性饮食帮助肠道菌群与炎症管理。",
+      "priority": 2,
+      "chapter_path": "references/modules/02_diet.md",
+      "keywords": ["fasting", "间歇性禁食", "进食窗口", "血糖", "肠道菌群", "发酵食品", "地中海饮食"],
+      "mechanisms": [
+        "进食状态偏向血糖较高、细胞复制与成长；禁食状态偏向修复、清理和自噬。",
+        "稳定进食窗口与睡眠周期对齐，避免类似频繁倒时差的代谢扰动。",
+        "肠道菌群多样性与消化、免疫和炎症相关；抗生素会显著破坏菌群生态。"
+      ],
+      "practices": [
+        "基础禁食：起床后至少 1 小时不吃，睡前 2-3 小时不吃。",
+        "高阶禁食：逐步尝试 8 小时进食窗口，如 10-18 点或 12-20 点。",
+        "禁食期间可喝水、茶、黑咖啡；糖会中断禁食。",
+        "晚饭后轻量散步帮助血糖清理。",
+        "每天两次摄入自然发酵食品，如无糖酸奶、kefir、康普茶、泡菜、纳豆。",
+        "日常饮食以植物类食物为主，减少深度加工食品和糖。"
+      ],
+      "cautions": [
+        "长时间禁食、胆结石风险、糖尿病、低血糖、孕产或进食障碍相关情况应先咨询医生。",
+        "益生菌和益生元效果并非总是可靠，产品监管有限。",
+        "生酮饮食长期实践可能存在风险；README 更推荐可持续的地中海饮食结构。"
+      ],
+      "assets": [],
+      "references": [
+        {"title": "Christopher Gardner diet comparison", "url": "https://youtu.be/sJLK3sVexIk", "role": "diet comparison"},
+        {"title": "中国居民膳食指南介绍", "url": "https://sspai.com/post/72984", "role": "localized dietary reference"},
+        {"title": "Bloch fasting gallbladder paper", "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1419405/", "role": "risk discussion"},
+        {"title": "Sichieri overnight fasting paper", "url": "https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1405175/", "role": "risk discussion"}
+      ]
+    },
+    {
+      "id": "mindset_dopamine",
+      "title": "心态、动力与多巴胺",
+      "summary": "本模块把多巴胺视为动机、欲望、快乐和坚持的核心调节系统，重点是避免过度叠加刺激，建立随机奖励和成长型思维。",
+      "priority": 3,
+      "chapter_path": "references/modules/03_mindset_dopamine.md",
+      "keywords": ["多巴胺", "动力", "成长型思维", "奖励", "冷水浴", "上瘾"],
+      "mechanisms": [
+        "多巴胺的相对变化量比绝对水平更影响主观快乐；持续高刺激会抬高快乐阈值。",
+        "多巴胺储备有限，工作、游戏、社交、运动等活动会竞争同一套奖励系统。",
+        "刺激叠加会形成更高峰值，也可能带来更长低谷，削弱单一活动本身的吸引力。"
+      ],
+      "practices": [
+        "对常规活动随机化奖励叠加因素，例如有时运动听音乐、有时不听。",
+        "把努力过程本身定义为奖励，用成长型思维降低对外部奖赏的依赖。",
+        "通过健康社交、运动、稳定睡眠等方式支持多巴胺系统。",
+        "必要时用冷水浴等行动工具，但控制频率并注意安全。"
+      ],
+      "cautions": [
+        "尼古丁、可卡因、安非他命和滥用聪明药会强烈扰动奖励系统并有成瘾风险。",
+        "L-Tyrosine、PEA、Huperzine A、Modafinil、Alpha-GPC 等不应持续随意使用。",
+        "夜间光照和褪黑素可能降低多巴胺相关状态，影响情绪和专注。"
+      ],
+      "assets": [],
+      "references": [
+        {"title": "Controlling Your Dopamine for Motivation, Focus and Satisfaction", "url": "https://hubermanlab.com/controlling-your-dopamine-for-motivation-focus-and-satisfaction/", "role": "primary topic source"}
+      ]
+    },
+    {
+      "id": "learning_focus",
+      "title": "学习、专注与神经可塑性",
+      "summary": "学习被描述为神经元重新连接，需要足够专注和犯错信号。成年人可通过小幅增量学习、前庭系统新颖刺激、休息和注意力环境设计来提升学习效率。",
+      "priority": 4,
+      "chapter_path": "references/modules/04_learning_focus.md",
+      "keywords": ["学习", "专注", "神经可塑性", "犯错", "生理叹息", "冥想", "手机使用"],
+      "mechanisms": [
+        "学习需要神经可塑性状态，犯错会释放肾上腺素、乙酰胆碱和多巴胺来促进调整。",
+        "神经元重连接主要在休息和睡眠中巩固。",
+        "Default network 与 Task networks 需要像跷跷板一样协调；多巴胺有助于专注网络协调。"
+      ],
+      "practices": [
+        "把学习拆成小幅增量，尤其适合 25 岁后神经可塑性下降的成年人。",
+        "用倒立、瑜伽、滑板等新颖平衡体验触发前庭系统，但必须注意安全。",
+        "压力过高时使用生理叹息：连续两次吸气后长呼气。",
+        "90 分钟学习后进行约 20 分钟非睡眠深度休息。",
+        "限制视野干扰、提高显示器位置，减少 context switch。",
+        "控制手机时长；README 引用青少年少于 60 分钟、成年人少于 120 分钟的研究建议。"
+      ],
+      "cautions": [
+        "心流更适合执行已掌握任务，不等同于学习新技能的最佳状态。",
+        "聪明药可能带来成瘾、代谢和长期学习效果风险。",
+        "前庭刺激、倒立和冷水等行动工具有安全风险。"
+      ],
+      "assets": [],
+      "references": [
+        {"title": "Rich Roll interview with Andrew Huberman", "url": "https://youtu.be/2ekdc6jCu2E", "role": "background source"}
+      ]
+    },
+    {
+      "id": "brain_health",
+      "title": "大脑健康与营养支持",
+      "summary": "大脑健康模块强调睡眠、有氧运动、电解质和关键营养素。README 把 Omega-3 EPA、磷脂酰丝氨酸、胆碱等列为相对重要的支持项。",
+      "priority": 5,
+      "chapter_path": "references/modules/05_brain_health.md",
+      "keywords": ["大脑健康", "有氧运动", "Omega-3", "EPA", "胆碱", "肌酸", "电解质"],
+      "mechanisms": [
+        "有氧运动提升心肺功能，支持大脑供能。",
+        "Omega-3 EPA 是神经细胞重要组成部分，并与情绪和注意力支持相关。",
+        "水、钠、钾、镁等电解质是神经元信号传递的基础。"
+      ],
+      "practices": [
+        "每周 150-180 分钟有氧训练。",
+        "通过鱼、牡蛎、奇亚籽、核桃、大豆或鱼油补充 Omega-3 EPA。",
+        "通过鸡蛋尤其蛋黄、土豆、坚果、水果或 Alpha-GPC 获取胆碱来源。",
+        "不吃肉的人可关注肌酸摄入。",
+        "用心理暗示或与喜欢的食物搭配，逐步增加对健康食物的接受度。"
+      ],
+      "cautions": [
+        "补充剂剂量和适用性需结合饮食、疾病、药物和专业意见。",
+        "Alpha-GPC、肌酸等补充剂不应替代睡眠、运动和饮食基础。",
+        "个体对食物和补剂反应不同，应记录并复盘。"
+      ],
+      "assets": [],
+      "references": [
+        {"title": "Huberman supplements page", "url": "https://www.thorne.com/u/huberman", "role": "supplement example"}
+      ]
+    },
+    {
+      "id": "longevity",
+      "title": "长寿、抗衰老与风险边界",
+      "summary": "长寿模块来自 Huberman 与 David Sinclair 相关访谈，涵盖衰老机制、fasting、饮食、运动、药物、细胞重编程和监测。README 已在 2025-06-17 更新提醒 Sinclair 及白藜芦醇、NMN 等证据争议，应谨慎采纳。",
+      "priority": 6,
+      "chapter_path": "references/modules/06_longevity.md",
+      "keywords": ["长寿", "Sinclair", "fasting", "mTOR", "sirtuin", "NMN", "白藜芦醇", "二甲双胍", "Yamanaka Factors"],
+      "mechanisms": [
+        "README 将衰老描述为 DNA 信息和表观基因组控制信息损失，其中表观基因组占较大权重。",
+        "低血糖状态可能抑制 mTOR、激活 sirtuin、提高胰岛素敏感度并触发修复。",
+        "现代长寿研究更关注触发身体自身的抗衰老机制，而不是简单外源抗氧化。"
+      ],
+      "practices": [
+        "长寿饮食倾向植物类蛋白和脂肪，减少精制碳水、糖、动物脂肪和动物蛋白。",
+        "每周约 3 小时有氧，搭配 2-3 次力量训练。",
+        "跟踪 HbA1c、CRP、LDL 等指标，并由专业人员解释。",
+        "避免吸烟、肥胖和不必要的 X 光暴露。",
+        "把药物和补充剂视为高风险候选项，不作为默认生活计划。"
+      ],
+      "cautions": [
+        "Sinclair 相关主张、白藜芦醇、NMN、NR、二甲双胍等抗衰老方案存在较大争议。",
+        "药物研究多处于人体实验早期或适应症外讨论，不能自行处方。",
+        "长期或极端禁食可能增加胆结石、低血糖或其他风险。",
+        "长寿指标和医学范围需要个性化，不能只看通用参考区间。"
+      ],
+      "assets": [
+        "imgs/diet_for_longevity.png",
+        "imgs/workout_plan.png",
+        "imgs/drugs_for_longevity.png",
+        "imgs/cell_reprogramming.png"
+      ],
+      "references": [
+        {"title": "Nutrition, longevity and disease", "url": "https://www.cell.com/cell/pdf/S0092-8674(22)00398-1.pdf", "role": "diet and longevity paper"},
+        {"title": "The quest to slow ageing through drug discovery", "url": "https://www.nature.com/articles/s41573-020-0067-7", "role": "drug discovery overview"},
+        {"title": "程序员延寿指南", "url": "https://github.com/geekan/HowToLiveLonger", "role": "external Chinese longevity guide"},
+        {"title": "Life Biosciences", "url": "https://www.lifebiosciences.com/", "role": "company example"},
+        {"title": "Altos Labs", "url": "https://altoslabs.com/", "role": "company example"}
+      ]
+    },
+    {
+      "id": "personal_practice",
+      "title": "个人实践与工具化训练",
+      "summary": "README 最后把作者实践整理成可训练习惯：早晨光照、8 小时进食窗口、EPA 鱼油、专注模式、站立办公、Yoga Nidra、每周运动和 PAI 监控。",
+      "priority": 7,
+      "chapter_path": "references/modules/07_personal_practice.md",
+      "keywords": ["个人实践", "习惯", "PAI", "AG1", "鱼油", "站立办公", "运动"],
+      "mechanisms": [
+        "把复杂健康知识转为低摩擦日常动作，更容易形成习惯训练。",
+        "通过手环、App、阅读时长和专注模式等外部工具降低执行成本。",
+        "运动、饮食、睡眠、学习互相影响，晚间运动可能改善精神但损害睡眠。"
+      ],
+      "practices": [
+        "早晨遛狗或通勤时完成自然光暴露。",
+        "尝试 8 小时进食窗口，中午偏蔬菜轻食，早上可喝盐水、茶或补剂。",
+        "优先考虑广泛认可的基础补充剂，如复合维生素和 EPA 鱼油。",
+        "用专注模式、番茄时钟、升降桌和 Yoga Nidra 支持工作学习。",
+        "用小米手环 PAI 或类似指标保持每周约 3 次跑步/羽毛球等运动。"
+      ],
+      "cautions": [
+        "作者实践不是通用处方，需根据个人健康、家庭、工作和医学条件调整。",
+        "AG1、白藜芦醇、NMN、二甲双胍等在 README 中均带有性价比或证据争议提醒。",
+        "下班后 21-22 点运动可能影响睡眠质量，需要权衡。"
+      ],
+      "assets": [],
+      "references": [
+        {"title": "My Circadian Clock App", "url": "https://mycircadianclock.org/", "role": "tracking tool"},
+        {"title": "Huberman supplement list", "url": "https://fastlifehacks.com/andrew-huberman-supplements-list/", "role": "supplement reference"},
+        {"title": "养生博主的 23 年总结", "url": "https://zhuanlan.zhihu.com/p/675470252", "role": "update article"},
+        {"title": "养生博主的 24 年总结", "url": "https://zhuanlan.zhihu.com/p/1896275046068094483", "role": "update article"}
+      ]
+    }
+  ],
+  "references": [
+    {"title": "Huberman Lab", "url": "https://hubermanlab.com/", "role": "primary source collection"},
+    {"title": "Lex Fridman daily routine article", "url": "https://zhuanlan.zhihu.com/p/371254789", "role": "background"},
+    {"title": "视频版", "url": "https://www.bilibili.com/video/BV1EW4y1R7yi/", "role": "README video summary"},
+    {"title": "养生博主的 23 年总结", "url": "https://zhuanlan.zhihu.com/p/675470252", "role": "author update"},
+    {"title": "养生博主的 24 年总结", "url": "https://zhuanlan.zhihu.com/p/1896275046068094483", "role": "author update"}
+  ],
+  "graph": {
+    "nodes": [
+      {"id": "sleep", "label": "睡眠", "type": "module", "detail": "健康、学习、代谢和情绪的基础。"},
+      {"id": "diet", "label": "饮食/禁食", "type": "module", "detail": "进食窗口、血糖状态、肠道菌群和饮食结构。"},
+      {"id": "dopamine", "label": "多巴胺", "type": "mechanism", "detail": "动机、奖励、快乐阈值和专注协调。"},
+      {"id": "focus", "label": "学习专注", "type": "module", "detail": "犯错信号、神经可塑性、休息和注意力环境。"},
+      {"id": "brain", "label": "大脑健康", "type": "module", "detail": "有氧运动、Omega-3、胆碱、电解质。"},
+      {"id": "longevity", "label": "长寿", "type": "module", "detail": "饮食、运动、监测、药物争议和细胞重编程。"},
+      {"id": "practice", "label": "个人实践", "type": "module", "detail": "把知识转成低摩擦日常习惯。"},
+      {"id": "light", "label": "晨间光照", "type": "practice", "detail": "起床后户外 2-10 分钟。"},
+      {"id": "night_light", "label": "夜间避光", "type": "practice", "detail": "尤其避免 23:00-04:00 强光。"},
+      {"id": "fasting", "label": "进食窗口", "type": "practice", "detail": "基础版睡前 2-3 小时不吃，高阶 8 小时窗口。"},
+      {"id": "fermented", "label": "发酵食品", "type": "practice", "detail": "每天两次自然发酵食品，支持菌群多样性。"},
+      {"id": "exercise", "label": "有氧+力量", "type": "practice", "detail": "每周约 150-180 分钟有氧，搭配力量训练。"},
+      {"id": "nsdr", "label": "NSDR/冥想", "type": "practice", "detail": "午休、Yoga Nidra、生理叹息和深度休息。"},
+      {"id": "caution_drugs", "label": "药物/补剂争议", "type": "risk", "detail": "NMN、白藜芦醇、二甲双胍、聪明药等需谨慎。"},
+      {"id": "medical", "label": "医学边界", "type": "risk", "detail": "药物、慢病、异常指标、极端禁食需要专业意见。"}
+    ],
+    "edges": [
+      {"source": "light", "target": "sleep", "relation": "校准昼夜节律"},
+      {"source": "night_light", "target": "sleep", "relation": "降低节律扰动"},
+      {"source": "sleep", "target": "dopamine", "relation": "夜间光照会影响后续多巴胺状态"},
+      {"source": "dopamine", "target": "focus", "relation": "支持动机和专注网络协调"},
+      {"source": "sleep", "target": "focus", "relation": "睡眠中巩固学习"},
+      {"source": "nsdr", "target": "focus", "relation": "降低压力并支持学习恢复"},
+      {"source": "fasting", "target": "diet", "relation": "控制进食时间和血糖状态"},
+      {"source": "fermented", "target": "diet", "relation": "提升肠道菌群多样性"},
+      {"source": "exercise", "target": "brain", "relation": "有氧支持大脑供能"},
+      {"source": "exercise", "target": "longevity", "relation": "心肺和肌肉能力支持延寿"},
+      {"source": "diet", "target": "longevity", "relation": "饮食结构和禁食影响衰老机制"},
+      {"source": "practice", "target": "sleep", "relation": "晨光和夜间避光可训练"},
+      {"source": "practice", "target": "diet", "relation": "进食窗口可训练"},
+      {"source": "practice", "target": "focus", "relation": "专注块和阅读可训练"},
+      {"source": "caution_drugs", "target": "longevity", "relation": "NMN/白藜芦醇/二甲双胍需谨慎"},
+      {"source": "medical", "target": "caution_drugs", "relation": "涉及药物和异常指标需专业意见"},
+      {"source": "medical", "target": "fasting", "relation": "极端禁食需专业评估"}
+    ]
+  }
+}
--- a/skill/references/modules/01_sleep.md
+++ b/skill/references/modules/01_sleep.md
@ -0,0 +1,29 @@
+# 睡眠与昼夜节律
+
+## 定位
+
+睡眠是本仓库健康系统优化的第一优先级。它影响免疫、代谢、心理状态、专注、学习巩固和运动恢复。README 的核心观点是：先把昼夜节律稳定住，再讨论饮食、专注、运动和补充剂。
+
+## 关键机制
+
+- 早晨光照通过黑视素神经节细胞校准生物钟，推动皮质醇和肾上腺素释放，并设定十多个小时后的褪黑素倒计时。
+- 夜间强光，尤其 23:00 到次日 04:00 的光照，会让身体误判为白天，影响后续情绪、专注、学习和代谢状态。
+- 体温上升偏向清醒，体温下降偏向睡眠。冷水澡、运动、环境温度和智能床垫都可通过体温影响节律。
+
+## 可执行习惯
+
+- 起床后到户外接触阳光 2-10 分钟；隔窗日光效果显著降低。
+- 晚上减少强光和手机光，必要时使用低位暗红光或 blue blockers。
+- 傍晚看落日，给身体一个夜间即将到来的时间信号。
+- 中午后咖啡因是否影响睡眠要个人测试；默认先谨慎。
+- 用午睡、Yoga Nidra、冥想或自我催眠替代硬撑。
+
+## 风险边界
+
+- 不把褪黑素作为常规入睡方案；README 提到剂量监管和抑郁情绪风险。
+- 镁、芹黄素、牛磺酸等补充剂应结合个人状态和专业意见。
+- 晚间高强度运动可能推迟体温下降，若影响入睡，需要调整时段或强度。
+
+## 适合 agent 的回答要点
+
+回答睡眠问题时，优先询问作息、晨间光照、夜间光照、咖啡因、运动时间和午休方式。制定计划时，先给低风险零成本动作，再讨论补充剂和设备。
--- a/skill/references/modules/02_diet.md
+++ b/skill/references/modules/02_diet.md
@ -0,0 +1,31 @@
+# 饮食、禁食与肠道健康
+
+## 定位
+
+饮食模块强调两件事：何时进食与吃什么同等重要；肠道菌群是消化、免疫和炎症状态的重要调节因素。
+
+## 关键机制
+
+- 进食状态通常血糖较高，身体更偏向细胞复制和成长。
+- 禁食状态血糖较低，身体更偏向修复、清理和自噬。
+- 稳定进食窗口与睡眠周期对齐，避免类似频繁倒时差的代谢扰动。
+- 肠道菌群多样性通常是更健康的信号；抗生素会严重破坏菌群生态。
+
+## 可执行习惯
+
+- 基础版：起床后至少 1 小时不吃，睡前 2-3 小时不吃。
+- 高阶版：逐步缩短到 8 小时进食窗口，如 10-18 点或 12-20 点。
+- 禁食期间可喝水、茶、黑咖啡；糖会中断禁食。
+- 晚饭后散步，帮助血糖清理。
+- 每天两次摄入自然发酵食品，如无糖酸奶、kefir、康普茶、泡菜、纳豆。
+- 日常饮食以植物类食物为主，减少糖和深加工食品。
+
+## 风险边界
+
+- 长时间禁食、糖尿病、低血糖、胆结石、孕产、进食障碍、慢病用药等情况，需要医生或专业营养师参与。
+- 益生菌和益生元的效果并不稳定，产品监管有限。
+- README 更倾向推荐可持续的地中海饮食结构，而不是长期严格生酮。
+
+## 适合 agent 的回答要点
+
+帮助用户制定饮食计划时，先确认睡眠时段、工作社交约束、运动目标和既往疾病。优先给稳定进食窗口、减少糖、增加发酵食品和植物性食物的低风险建议。
--- a/skill/references/modules/03_mindset_dopamine.md
+++ b/skill/references/modules/03_mindset_dopamine.md
@ -0,0 +1,29 @@
+# 心态、动力与多巴胺
+
+## 定位
+
+本模块解释为什么人会有动力、快乐、上瘾、倦怠和放弃。它支撑后续习惯训练：不要只靠意志力，要设计奖励系统。
+
+## 关键机制
+
+- 多巴胺的相对变化量比绝对值更影响快乐感。
+- 多巴胺储备有限，工作、游戏、社交、运动和药物刺激会竞争同一套奖励系统。
+- 刺激叠加会带来更高峰值，也可能带来更长低谷，并削弱活动本身的吸引力。
+- 成长型思维可以把努力过程本身重新标记为奖励。
+
+## 可执行习惯
+
+- 对常规活动随机化奖励叠加因素，例如运动时有时听音乐、有时不听。
+- 避免每次学习、运动或工作都叠加咖啡因、音乐、社交、社媒展示等奖励。
+- 把“我正在变强”而不是“完成后奖励自己”作为努力时的主叙事。
+- 用睡眠、健康社交、运动等基础行为维护奖励系统。
+
+## 风险边界
+
+- 尼古丁、可卡因、安非他命和滥用聪明药存在成瘾和系统扰动风险。
+- L-Tyrosine、PEA、Huperzine A、Modafinil、Alpha-GPC 等不应持续随意使用。
+- 冷水浴有安全风险，不适合所有人，也不需要高频执行。
+
+## 适合 agent 的回答要点
+
+当用户问自律、拖延、上瘾或动力时，优先从睡眠、刺激叠加、奖励随机化、过程奖励和环境设计分析，不要直接推荐药物或补剂。
--- a/skill/references/modules/04_learning_focus.md
+++ b/skill/references/modules/04_learning_focus.md
@ -0,0 +1,31 @@
+# 学习、专注与神经可塑性
+
+## 定位
+
+学习被视为神经元重新连接。专注、犯错、休息和睡眠共同决定学习效率。
+
+## 关键机制
+
+- 犯错信号会释放肾上腺素、乙酰胆碱和多巴胺，使大脑进入可塑性状态。
+- 心流适合执行已掌握任务，不等同于学习新东西的最佳状态。
+- 休息和睡眠是神经元重连接的重要窗口。
+- Default network 与 Task networks 的协调影响专注能力。
+
+## 可执行习惯
+
+- 成年人学习新技能时，把任务拆成小幅增量。
+- 使用安全的新颖平衡体验，如初级瑜伽、平衡训练，触发前庭系统的新颖信号。
+- 压力过高时使用生理叹息：两次吸气后长呼气。
+- 每 90 分钟学习后进行约 20 分钟非睡眠深度休息。
+- 限制视野干扰，减少通知和 context switch。
+- 控制手机使用时长，避免高频短视频切换损伤注意力。
+
+## 风险边界
+
+- 倒立、滑板、冷水等行动工具有安全门槛。
+- 聪明药不应作为长期学习策略。
+- 若存在 ADHD、焦虑、抑郁或睡眠障碍，应寻求专业评估。
+
+## 适合 agent 的回答要点
+
+制定学习计划时，要包含训练块、休息块、错误反馈、睡眠巩固和环境控制。不要只给时间表，也要设计如何处理挫败感。
--- a/skill/references/modules/05_brain_health.md
+++ b/skill/references/modules/05_brain_health.md
@ -0,0 +1,30 @@
+# 大脑健康与营养支持
+
+## 定位
+
+大脑健康模块把睡眠、有氧运动、电解质和关键营养素作为基础，不把补充剂放在第一位。
+
+## 关键机制
+
+- 有氧运动提升心肺能力，支持大脑供能。
+- Omega-3 EPA 是神经细胞的重要组成部分，也与情绪和注意力支持相关。
+- 乙酰胆碱是重要神经调质，影响注意力。
+- 水、钠、钾、镁等电解质是神经信号传递基础。
+
+## 可执行习惯
+
+- 每周累计 150-180 分钟有氧训练。
+- 通过鱼、牡蛎、奇亚籽、核桃、大豆或鱼油补充 Omega-3 EPA。
+- 通过鸡蛋尤其蛋黄、土豆、坚果、水果或 Alpha-GPC 获取胆碱来源。
+- 不吃肉的人关注肌酸摄入。
+- 通过心理暗示或与喜欢的食物搭配，逐步提高健康食物接受度。
+
+## 风险边界
+
+- 补充剂剂量和适用性取决于饮食、疾病、药物和体检指标。
+- Alpha-GPC、肌酸、鱼油等不能替代睡眠、运动和饮食结构。
+- 对海鲜、鸡蛋或特定补剂过敏的人需要替代方案。
+
+## 适合 agent 的回答要点
+
+回答大脑健康问题时，先看睡眠、运动和饮食结构，再讨论补剂。补剂建议要带剂量不确定性和专业咨询边界。
--- a/skill/references/modules/06_longevity.md
+++ b/skill/references/modules/06_longevity.md
@ -0,0 +1,38 @@
+# 长寿、抗衰老与风险边界
+
+## 定位
+
+长寿模块覆盖饮食、运动、药物、细胞重编程和监测，但它也是本仓库风险最高、争议最多的部分。README 已在 2025-06-17 更新提醒 David Sinclair 及白藜芦醇、NMN 等抗衰产品存在较大争议。
+
+## 关键机制
+
+- README 将衰老描述为 DNA 信息和表观基因组控制信息损失。
+- 低血糖状态可能抑制 mTOR、激活 sirtuin，提高胰岛素敏感度并触发修复。
+- 长寿研究关注触发身体自身抗衰机制，而不是简单依赖外源抗氧化剂。
+- 山中因子和细胞重编程属于前沿技术，不是日常可执行习惯。
+
+## 可执行习惯
+
+- 饮食倾向植物类蛋白和脂肪，减少精制碳水、糖、动物脂肪和动物蛋白。
+- 每周约 3 小时有氧，搭配 2-3 次力量训练。
+- 关注 HbA1c、CRP、LDL 等指标，并由专业人员解释。
+- 避免吸烟、肥胖和不必要的 X 光暴露。
+- 把药物和补充剂放在高风险候选项，而不是默认计划。
+
+## 图片资产
+
+- `imgs/diet_for_longevity.png`：长寿饮食建议。
+- `imgs/workout_plan.png`：力量训练计划。
+- `imgs/drugs_for_longevity.png`：长寿药物研究概览。
+- `imgs/cell_reprogramming.png`：山中因子与细胞重编程。
+
+## 风险边界
+
+- 白藜芦醇、NMN、NR、二甲双胍等抗衰方案存在证据争议或适应症边界。
+- 药物研究多处于人体实验早期或适应症外讨论，不能自行处方。
+- 长时间或极端禁食可能增加胆结石、低血糖或其他风险。
+- 医学指标需要个性化解释，不能只看通用参考范围。
+
+## 适合 agent 的回答要点
+
+回答长寿问题时，先给睡眠、运动、饮食、戒烟和体检监控等高共识建议。涉及药物、补剂、基因治疗和细胞重编程时必须明确争议和医生边界。
--- a/skill/references/modules/07_personal_practice.md
+++ b/skill/references/modules/07_personal_practice.md
@ -0,0 +1,31 @@
+# 个人实践与工具化训练
+
+## 定位
+
+本模块把 README 的理论知识转成作者个人实践：晨间光照、进食窗口、补充剂、专注工具、运动监控和睡眠权衡。它适合作为后续为用户生成生活计划的模板来源。
+
+## 实践清单
+
+- 早晨遛狗或通勤时完成自然光暴露。
+- 尝试 8 小时进食窗口，中午偏蔬菜轻食。
+- 早上根据情况喝盐水、茶或 AG1 等补剂。
+- 基础补充剂优先考虑复合维生素和 EPA 鱼油。
+- 工作学习使用专注模式、番茄时钟、升降桌和 Yoga Nidra。
+- 每天保持 30 分钟以上阅读或学习。
+- 用手环 PAI 等指标维持每周约 3 次跑步、羽毛球或类似运动。
+
+## 关键权衡
+
+- 下班后 21-22 点运动能改善精神状态，但可能影响睡眠。
+- 补剂存在证据、价格和适用性差异，不能替代基础习惯。
+- 家庭、工作和身体状态会限制理想计划，需要先保证可持续。
+
+## 风险边界
+
+- 作者实践不是通用处方。
+- AG1、白藜芦醇、NMN、二甲双胍等在 README 中均带有性价比或证据争议提醒。
+- 若生活计划涉及药物、疾病、异常指标或极端饮食，应升级到专业建议。
+
+## 适合 agent 的回答要点
+
+给用户做计划时，优先建立“最小可执行版本”：晨光、固定睡眠窗口、基础禁食、每周运动、低糖和专注块。等用户能稳定执行，再叠加补剂、监测和高级策略。
--- a/skill/references/references.json
+++ b/skill/references/references.json
@ -0,0 +1,7 @@
+[
+  {"title": "Huberman Lab", "url": "https://hubermanlab.com/", "role": "primary source collection"},
+  {"title": "Controlling Your Dopamine for Motivation, Focus and Satisfaction", "url": "https://hubermanlab.com/controlling-your-dopamine-for-motivation-focus-and-satisfaction/", "role": "dopamine source"},
+  {"title": "Nutrition, longevity and disease", "url": "https://www.cell.com/cell/pdf/S0092-8674(22)00398-1.pdf", "role": "longevity diet paper"},
+  {"title": "The quest to slow ageing through drug discovery", "url": "https://www.nature.com/articles/s41573-020-0067-7", "role": "longevity drug overview"},
+  {"title": "程序员延寿指南", "url": "https://github.com/geekan/HowToLiveLonger", "role": "Chinese longevity reference"}
+]
--- a/skill/references/schema.json
+++ b/skill/references/schema.json
@ -0,0 +1,51 @@
+{
+  "$schema": "https://json-schema.org/draft/2020-12/schema",
+  "title": "HumanSystemOptimization Knowledge Base",
+  "type": "object",
+  "required": ["version", "source", "medical_boundary", "modules", "references", "graph"],
+  "properties": {
+    "version": {"type": "string"},
+    "source": {"type": "string"},
+    "medical_boundary": {"type": "string"},
+    "tracking_metrics": {"type": "array", "items": {"type": "string"}},
+    "modules": {
+      "type": "array",
+      "items": {
+        "type": "object",
+        "required": ["id", "title", "summary", "priority", "chapter_path", "mechanisms", "practices", "cautions", "references"],
+        "properties": {
+          "id": {"type": "string"},
+          "title": {"type": "string"},
+          "summary": {"type": "string"},
+          "priority": {"type": "integer"},
+          "chapter_path": {"type": "string"},
+          "keywords": {"type": "array", "items": {"type": "string"}},
+          "mechanisms": {"type": "array", "items": {"type": "string"}},
+          "practices": {"type": "array", "items": {"type": "string"}},
+          "cautions": {"type": "array", "items": {"type": "string"}},
+          "assets": {"type": "array", "items": {"type": "string"}},
+          "references": {
+            "type": "array",
+            "items": {
+              "type": "object",
+              "required": ["title", "url", "role"],
+              "properties": {
+                "title": {"type": "string"},
+                "url": {"type": "string"},
+                "role": {"type": "string"}
+              }
+            }
+          }
+        }
+      }
+    },
+    "graph": {
+      "type": "object",
+      "required": ["nodes", "edges"],
+      "properties": {
+        "nodes": {"type": "array"},
+        "edges": {"type": "array"}
+      }
+    }
+  }
+}